Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
904
datasets available to search
ShareScore release 0.9.0
Dataset results
904 results for “Biosynthesis”
Fig. 2 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 2. Genes involved in Paris saponin biosynthesis. (a) Genes participated in the MVA and MEP pathways. (b) Genes participated in the downstream of saponin backbone biosynthesis.
Fig. 4 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 4. An overview of DEG expression patterns and GO enrichments. (a) Heatmap of expression values for all DEGs. (b) GO enrichments of DEGs, with displaying the top fifteen subcategories for each category.
Fig. 7 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 7. QRT-PCR validation of RNA-Seq data. Expression profiles of eight selected genes were determined by transcriptome and qRT-PCR data. The left vertical axis represents the relative expression of the gene based on qRT-PCR. The right vertical axis represents the expression level of the gene based on transcriptome sequencing. The asterisk above the bar chart denotes statistical significance based on the qRT-PCR data (* denotes P value <0.05, ** denotes P value <0.01, ns denotes P value> 0.05).
Fig. 1 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 1. The bioactive compound content and transcriptome characters. (a) Total content of three typical types of Paris saponins in leaves and rhizomes during the vegetative and fruiting stages. VL: leaves at vegetative stage, VR: rhizomes at vegetative stage, FL: leaves at fruiting stage, and FR: rhizomes at fruiting stage. (b) Proportion of three types of Paris saponins in leaves and rhizomes. (c) Distribution of the expressed unigenes in tissues during the two stages (log2 (TPMþ1)> 0). (d) Boxplot of unigene expression profiles.
Fig. 3 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 3. DEG statistics. (a) Venn diagram of DEGs from the four paired comparisons. (b) The number of up-down regulated DEGs of the four paired comparisons.
Fig. 4 in Characterization of the stearoyl-ACP desaturase gene (PoSAD) from woody oil crop Paeonia ostii var. lishizhenii in oleic acid biosynthesis
Fig. 4. Quantification of fatty acids in the developing endosperm of P. ostii var. lishizhenii. The FA contents (A) and composition (B) in the developing endosperm of P. ostii var. lishizhenii. The graph shows average values of three replicates with the respective error bars indicating standard deviations. Different letters above the columns indicate significant differences at P<0.05.
Fig. 5 in Characterization of the stearoyl-ACP desaturase gene (PoSAD) from woody oil crop Paeonia ostii var. lishizhenii in oleic acid biosynthesis
Fig. 5. The fatty acid contents (A) and the ratios of PA/POA and SA/OA (B) in pYES2-PoSAD and pYES2 transgenic INVSc1. The graph shows average values of three replicates with the respective error bars indicating standard deviations. Different letters above the columns indicate significant differences at P <0.05.
Fig. 3 in Characterization of the stearoyl-ACP desaturase gene (PoSAD) from woody oil crop Paeonia ostii var. lishizhenii in oleic acid biosynthesis
Fig. 3. Relative expression levels of PoSAD by qRT-PCR. The data show the relative gene expression of PoSAD in Paeonia ostii var. lishizhenii roots, leaves, shoots, stems, petals, stamens and seven development stages of endosperm (S1~S7). The graph shows average values of three replicates with the respective error bars indicating standard deviations.
Fig. 2 in Characterization of the stearoyl-ACP desaturase gene (PoSAD) from woody oil crop Paeonia ostii var. lishizhenii in oleic acid biosynthesis
Fig. 2. Phylogenetic analysis of plant stearoyl-ACP desaturase. The position of PoSAD is marked by a bold black dot. Plant species included in the phylogenetic tree are: Arabidopsis thaliana, Camellia sinensis, Camellia oleifera, Citrus clementina, Corchorus capsularis, Citrus sinensis, Citrus unshiu, Coffea arabica, Herrania umbratica, Manihot esculenta, Macadamia tetraphylla, Nelumbo nucifera, Oryza sativa, Paeonia lactiflora, Paeonia ludlowii, Panicum miliaceum, Populus alba, Populus euphratica, Populus trichocarpa, Ricinus communis, Setaria italica, Theobroma cacao, Triticum aestivum, Vernicia montana, Vitis vinifera, Zea mays and Ziziphus jujube.
Fig. 6 in Characterization of the stearoyl-ACP desaturase gene (PoSAD) from woody oil crop Paeonia ostii var. lishizhenii in oleic acid biosynthesis
Fig. 6. Fatty acid analysis of A. thaliana seeds. (A) FA contents in the seeds of wild-type, empty and three different PoSAD overexpressing transgenic A. thaliana lines. (B) FA composition in the seed oils of wild-type, empty and three different PoSAD overexpressing transgenic A. thaliana lines. The graph shows average values of three replicates with the respective error bars indicating standard deviations. Different letters above the columns indicate significant differences at P<0.05.
Fig. 7 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 7. Effect of endophyte (s) and TV1 colonization alone or in co-inoculation on photosynthetic pigments. (a) chlorophyll a, (b) chlorophyll b, and (c) carotenoids. Standard deviation of mean (SD) of three biological replicates. Asterisks indicate a significant variance between control and treatment plants (*p <0.05, **p <0.01).
Fig. 5 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 5. Impact of RF1+TV1 combination on forskolin pathway genes analyzed by Real-time qPCR. Data are mean ±SD (n =3 replicates). The relative quantity (RQ) of each gene was estimated using the formula RQ =2-ΔΔCt. Expression level of gene (a) CfTPS1, (b) CfTPS2, (c) CfTPS3, (d) CfTPS4, (e) CfCYP76AH15 and (f) CfACT1- 8. Asterisks indicate significant variation between control and endophyte inoculations (**p <0.01).
Fig. 4 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 4. Schematic representation of forskolin biosynthetic pathway. Inoculation of CFRF1+TV1 combination differentially modulated the expression of different genes involved in forskolin biosynthesis. Intensity of grey to dark color with circles indicates expression level of specific gene in control (C) and RF1+TV1 (R + T) treated plants (i. e., grey color less expression and dark color more expression). The higher expression of CfTPS2 and CfACT1-8 followed by CfCY- P76AH15, CfTPS4, and CfTPS3.
Fig. 3 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 3. Forskolin relative yield in various treatments tested under field conditions were analyzed by TLC method. (a) TLC plate and (b) graphical view of forskolin relative yield in roots. F: forskolin standard, Con: control, T1: RF1, T2: SF1, T3: SF2, T4: TV1, T5: RF1 + TV1, T6: SF1 + TV1 and T7: SF2 + TV1. Standard deviation of mean (SD). Asterisks indicate a significant variation between control and treatment plants (*p <0.05, **p <0.01).
Fig. 2 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 2. Effect of endophytes and TV1 colonization on C. forskohlii. The beneficial effects of various treatments on plant height, branch number and total biomass. The graphical bar represents the effect of total of seven treatments, RF1, SF1, SF2, TV1, RF1+TV1, SF1+TV1, and SF2+TV2 and one control. (a) Plant height and (b) Number of branches. The fresh weights of shoots and roots (c) and dry weights of shoots and roots (d) were analyzed. The root length and number of tuberous roots per plant also recorded from 4 biological replicates. Error bars represents the standard deviation of mean (SD). Asterisks indicate a significant difference between control and endophyte treatments (*p <0.05, **p <0.01).
Fig. 1 in Molecular insights of fungal endophyte co-inoculation with Trichoderma viride for the augmentation of forskolin biosynthesis in Coleus forskohlii
Fig. 1. Scanning electron microscopic images of fungal endophytes, P. cornearis (SF1), M. pseudophaseolina (SF2), and F. redolens (RF1) grown on PDA. The magnified images of conidia and mycelia were captured. SF1 (A) and SF1 (B) are magnified images of chlamydospore (arrows) and scale = 10 μM (5000 ×) and 5 μM (10000 ×), respectively. SF2 (A) and SF2 (B) are magnified images of mycelia (arrows) and scale = 20 μM (2500 ×) and 5 μM (10000 ×), respectively. RF1 (A) and RF1 (B) are magnified images of chlamydospore (arrow) and scale = 5 μM (10000 ×) and 2 μM (20000 ×), respectively.
Fig. 4 in A pair of threonines mark ent-kaurene synthases for phytohormone biosynthesis
Fig. 4. TT motif is not required for the production of ent-kaurene (1). Extracted ion (m/z = 272) chromatograms demonstrating the production of 1 by all mutants (as indicated) by comparison to wild-type (WT) AtKS.
Fig. 5 in A pair of threonines mark ent-kaurene synthases for phytohormone biosynthesis
Fig. 5. TT motif has minimal effect on catalytic efficiency. Curve fit of Michaelis-Menton equation to data for wild-type (WT) and indicated mutants of AtKS.
Fig. 6 in Enhancement of antroquinonol production via the overexpression of 4-hydroxybenzoate polyprenyltransferase biosynthesis-related genes in Antrodia cinnamomea
Fig. 6. Time profiles of the contents of AQ (A) and biomass (B) in the pCT74- gpd, pCT74-gpd-ubiA, and pCT74-gpd-CoQ2 transformants under submerged culture condition. a-c Different lower-case letters indicate a significant difference (p <0.05).
Fig. 4 in Enhancement of antroquinonol production via the overexpression of 4-hydroxybenzoate polyprenyltransferase biosynthesis-related genes in Antrodia cinnamomea
Fig. 4. The relative mRNA expression levels of the ubiA (A) and CoQ2 (B) genes. Expression levels in the pCT74-gpd strain samples are defined as 1.0, and expression levels in the transgenic strain are displayed as the fold increase over the reference sample. a-e Different lower-case letters indicate a significant difference (p <0.05).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.